15 citations · 35 across the 20 of their papers we have counts for
17 papers · 1 filter
Weak conditional propagation of chaos for systems of interacting particles with nearly stable jumps
Eva Löcherbach, Dasha Loukianova, Elisa Marini
We consider a system of interacting particles, described by SDEs driven by Poisson random measures, where the coefficients depend on the empirical measure of the system. Every…
Nonparametric estimation of the jump rate in mean field interacting systems of neurons
Aline Duarte, Kadmo Laxa, Eva Löcherbach +1
We consider finite systems of interacting neurons described by non-linear Hawkes processes in a mean field frame. Neurons are described by their membrane potential. They spike…
Strong propagation of chaos for systems of interacting particles with nearly stable jumps
Eva Löcherbach, Dasha Loukianova, Elisa Marini
We consider a system of interacting particles, described by SDEs driven by Poisson random measures, where the coefficients depend on the empirical measure of the system. Every…
Mean field limits of interacting particle systems with positive stable jumps
Dasha Loukianova, Eva Löcherbach
This note is a companion article to the recent paper Löcherbach, Loukianova, Marini (2024). We consider mean field systems of interacting particles. Each particle jumps with a jump…
Limit of the environment viewed from Sinaï's walk
Francis Comets, Oleg Loukianov, Dasha Loukianova
For Sinaï's walk (X_k) we show that the empirical measure of the environment seen from the particle (\bar\w_k) converges in law to some random measure S. This limit measure is expl…
Strong error bounds for the convergence to its mean field limit for systems of interacting neurons in a diffusive scaling
Xavier Erny, Eva Löcherbach, Dasha Loukianova
We consider the stochastic system of interacting neurons introduced in De Masi et al. (2015) and in Fournier and Löcherbach (2016) and then further studied in Erny, Löcherbach and…